Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Markus Dabernig"'
Publikováno v:
Frontiers in Climate, Vol 5 (2023)
IntroductionWith hydropower being the dominant source of renewable energy in Austria and recent years being disproportionally dry, alternative renewable energy sources need to be tapped to compensate for the reduction of fossil fuels and account for
Externí odkaz:
https://doaj.org/article/d25a9444e2654a9783cc76247c172faa
Publikováno v:
Meteorologische Zeitschrift, Vol 29, Iss 4, Pp 265-275 (2020)
Statistical post-processing is necessary to correct systematic errors of numerical weather prediction models, especially in complex terrains such as the Alps. However, this post-processing is usually applied on every grid point individually, which ca
Externí odkaz:
https://doaj.org/article/6749e067902b4a00814532061a37b8b7
Autor:
Irene Schicker, Markus Dabernig, Petrina Papazek, Theresa Schellander-Gorgas, Michael Tiefgraber
In the past decade, significant advances were made in improving the S2S and seasonal prediction using mainly numerical weather prediction models (NWP) and in some cases climate models for generating the predictions. Recently, the application of these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9f18174fe3118b1c9c73e2d44dcc2e9
https://doi.org/10.5194/egusphere-egu23-12949
https://doi.org/10.5194/egusphere-egu23-12949
Autor:
Jonas Bhend, Jonathan Demaeyer, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, Stéphane Vannitsem
Statistical postprocessing of forecasts from numerical weather prediction systems is an important component of modern weather forecasting systems. A growing variety of postprocessing methods has been proposed, but a comprehensive, community-driven co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b01e94cfa3f237dd17f50dde75ee6d30
https://doi.org/10.5194/egusphere-egu23-9328
https://doi.org/10.5194/egusphere-egu23-9328
Autor:
Jonathan Demaeyer, jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, Stéphane Vannitsem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffe14bfa90fe34851d398db8b5fdfbdc
https://doi.org/10.5194/essd-2022-465-supplement
https://doi.org/10.5194/essd-2022-465-supplement
Autor:
Jonathan Demaeyer, jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, Stéphane Vannitsem
Statistical postprocessing of medium-range weather forecasts is an important component of modern forecasting systems. Since the beginning of modern data science, numerous new postprocessing methods have been proposed, complementing an already very di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b6efdafe1d36885be41b79f4c0fa6a3
https://doi.org/10.5194/essd-2022-465
https://doi.org/10.5194/essd-2022-465
Publikováno v:
Meteorologische Zeitschrift, Vol 29, Iss 4, Pp 265-275 (2020)
Statistical post-processing is necessary to correct systematic errors of numerical weather prediction models, especially in complex terrains such as the Alps. However, this post-processing is usually applied on every grid point individually, which ca
Analogies between similar past forecasts, measurements, or analyses are a potentially useful tool when the training dataset is long enough, thus enabling an adequate identification of true analogs. Reducing the number of degrees of freedom in the mat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::273148b1401d80d01323b877d60af57b
https://www.bib.irb.hr/1246259
https://www.bib.irb.hr/1246259
Statistical postprocessing for weather forecasts review, challenges, and avenues in a big data world
Autor:
Jonas Bhend, Stephan Hemri, Zied Ben Bouallègue, Nigel Roberts, Leila Hieta, Bert Van Schaeybroeck, Kirien Whan, Lesley De Cruz, John Bjørnar Bremnes, Jussi Ylhaisi, Aitor Atencia, Jonathan Demaeyer, Markus Dabernig, Jonathan Flowerdew, Lionel Moret, Maurice Schmeits, Iris Odak Plenković, Olivier Mestre, Sebastian Lerch, Joris Van den Bergh, Gavin R. Evans, Maxime Taillardat, Stéphane Vannitsem, Susanne Theis
Publikováno v:
Bulletin of the American Meteorological Society
Bulletin of the American Meteorological Society, 2021, 102 (3), pp.E681-E699. ⟨10.1175/BAMS-D-19-0308.1⟩
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
Bulletin of the American Meteorological Society, 2021, 102 (3), pp.E681-E699. ⟨10.1175/BAMS-D-19-0308.1⟩
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of correcting the impact of different types of errors on the forecasts. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22e4387cbadc3565ff2d166301c77478
https://doi.org/10.1175/bams-d-19-0308.1
https://doi.org/10.1175/bams-d-19-0308.1
Numerical weather predictions are often too coarse to represent single turbines in a wind park and post-processing of the individual turbines is necessary. However, individual post-processing can lead to inconsistencies in forecasts for a wind farm.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aad966973c823febfada088310f3c9aa
https://doi.org/10.5194/egusphere-egu2020-16810
https://doi.org/10.5194/egusphere-egu2020-16810